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Subspecialties: Page 122
AI can detect cirrhosis accurately on MRI
By
Erik L. Ridley
An artificial intelligence (AI) algorithm can identify cirrhosis on standard T2-weighted liver MRI exams at a level comparable to that of an expert reader, offering promise as a tool for improving detection, German researchers reported in a presentation at the virtual 2020 RSNA meeting.
December 6, 2020
Machine learning helps identify cystic renal lesions
By
Erik L. Ridley
A machine-learning model based on CT radiomics analysis has achieved excellent diagnostic performance in distinguishing benign from malignant complex cystic renal lesions, outperforming the current Bosniak classification system, Canadian and French investigators reported at the RSNA 2020 meeting.
December 6, 2020
Use LDCT to screen for lung cancer, Germans say
By
AuntMinnieEurope.com staff writers
Using low-dose CT (LDCT) to screen for lung cancer in current and formerly heavy smokers offers more benefit than harm, according to the German Institute for Quality and Efficiency in Health Care.
December 3, 2020
Ibex Medical Analytics, Institut Curie partner on breast cancer
By
AuntMinnieEurope.com staff writers
Ibex Medical Analytics and Institut Curie are joining forces to improve breast cancer detection using artificial intelligence.
December 3, 2020
Perspectum MRI software helps guide liver surgeries
By
AuntMinnieEurope.com staff writers
MRI-based software developed by Perspectum provided information that could be useful in planning surgeries for liver cancer in an observational study published online on 2 December in
PLOS One
.
December 3, 2020
Dutch group shows how AI can find interval breast cancers
By
Theresa Pablos
Researchers from The Netherlands and the U.K. have used artificial intelligence (AI) software to pinpoint interval breast cancers. An AI program detected more than one-third of breast cancers missed on screening mammography in two different studies presented at RSNA 2020.
December 3, 2020
Keep aware of head and neck injuries in winter sports
By
Philip Ward
Radiologists need to know the essentials about head and neck, brain, and spinal injuries from skiing and snowboarding and about how CT and MRI can help in challenging cases, according to new research presented at the RSNA 2020 meeting by Swiss trauma experts.
December 2, 2020
Keep aware of head and neck injuries in winter sports
By
Philip Ward
Radiologists need to know the essentials about head and neck, brain, and spinal injuries from skiing and snowboarding and about how CT and MRI can help in challenging cases, according to new research presented at the RSNA 2020 meeting by Swiss trauma experts.
December 2, 2020
New algorithm can detect TB using a phone
By
AuntMinnieEurope.com staff writers
A deep learning-based tuberculosis (TB) detection model can detect TB on phone-captured chest x-ray photographs, a poster presented at the RSNA 2020 virtual conference revealed.
December 1, 2020
3D printing makes giant strides in liver
By
Philip Ward
3D models that combine vascular and biliary anatomy using different imaging techniques can contribute to more rigorous planning of complex liver operations, including hepatic resections, living-donor transplantation, vascular intervention procedures, and biliary reconstruction surgery, Portuguese researchers have reported at the RSNA 2020 meeting.
December 1, 2020
Chest experts unveil COVID-19 findings at RSNA meeting
By
Kate Madden Yee
CT is showing value in assessing the prevalence and severity of COVID-19 and evaluating ongoing conditions, especially when combined with artificial intelligence, according to presentations delivered by three thoracic specialists on Sunday at the RSNA 2020 virtual meeting.
November 29, 2020
RSNA awards Margulis prize to COVID-19 paper
By
AuntMinnieEurope.com staff writers
The RSNA has awarded its Alexander R. Margulis Award for Scientific Excellence to a radiologist in China who was one of the first to use CT to investigate a mysterious lung condition that later came to be known as COVID-19. The award recognizes the best original scientific paper of the year published in
Radiology.
November 29, 2020
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